Multi-Objective Evolutionary Path Planning for Unmanned Aerial Vehicles with Adjustable Imaging Angle
| Autor: | CHEN, GUAN-MIN, 陳冠㞶 |
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| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 105 An UAV, commonly known as a drone with various autonomy; either remote control or the self-piloting technology. Unmanned aerial vehicles has been already used in many military applications since many years. However, the uses of UAVs are now expanding in many commercial, scientific, recreational, agricultural, and civil applications, such as surveillance and remote photography. In order to make best uses of UAVs, there are many important research topics, one of the most important challenging questions is path planning of multiple UAVs. In this paper, we considered a surveillance application with 20 UAVs. There are three goals in this application, minimizing the total path of UAVs, minimizing the load balancing of UAVs, and maximizing the total coverage of surveillance demanding areas. A multi-objective evolutionary approach is proposed for planning unmanned aerial vehicles(UAVs) with adjustable imaging angle. of are considered in our problem. The campus of Chung-Hua University and five classical model are used as the environment of our problem. The results are compared with other evolutionary algorithms using the same number of function evaluations time. The experimental results are shown in the following tables and figures, the results indicate that the proposed multi-objective evolutionary algorithm outperform others algorithms in terms of convergence and solution quality. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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